Thaler, and Cass R. Sunstein: a revelatory look at how we make decisionsNew York Times bestsellerNamed a Best Book of the Year by The Economist and the Financial Times Every day we make choices—about what to buy or eat, about financial investments or our children’s health and education, even about the causes we champion or the planet itself. Unfortunately, we often choose poorly. Nudge is about how we make these choices and how we can make better ones. Using dozens of eye-opening examples and drawing on decades of behavioral science research, Nobel Prize winner Richard H. Thaler and Harvard Law School professor Cass R. Sunstein show that no choice is ever presented to us in a neutral way, and that we are all susceptible to biases that can lead us to make bad decisions. But by knowing how people think, we can use sensible “choice architecture” to nudge people toward the best decisions for ourselves, our families, and our society, without restricting our freedom of choice.

    With the sophisticated algorithms in this book, you can write smart programs to access interesting datasets from other web sites, collect data from users of your own applications, and analyze and understand the data once you've found it.Programming Collective Intelligence takes you into the world of machine learning and statistics, and explains how to draw conclusions about user experience, marketing, personal tastes, and human behavior in general -- all from information that you and others collect every day. Each algorithm is described clearly and concisely with code that can immediately be used on your web site, blog, Wiki, or specialized application. This book explains:Collaborative filtering techniques that enable online retailers to recommend products or media Methods of clustering to detect groups of similar items in a large dataset Search engine features -- crawlers, indexers, query engines, and the PageRank algorithm Optimization algorithms that search millions of possible solutions to a problem and choose the best one Bayesian filtering, used in spam filters for classifying documents based on word types and other features Using decision trees not only to make predictions, but to model the way decisions are made Predicting numerical values rather than classifications to build price models Support vector machines to match people in online dating sites Non-negative matrix factorization to find the independent features in a dataset Evolving intelligence for problem solving -- how a computer develops its skill by improving its own code the more it plays a game Each chapter includes exercises for extending the algorithms to make them more powerful. Go beyond simple database-backed applications and put the wealth of Internet data to work for you. "Bravo! I cannot think of a better way for a developer to first learn these algorithms and methods, nor can I think of a better way for me (an old AI dog) to reinvigorate my knowledge of the details."-- Dan Russell, Google "Toby's book does a great job of breaking down the complex subject matter of machine-learning algorithms into practical, easy-to-understand examples that can be directly applied to analysis of social interaction across the Web today. If I had this book two years ago, it would have saved precious time going down some fruitless paths."-- Tim Wolters, CTO, Collective Intellect

    Kathryn Schulz, editor of Grist magazine, argues that error is the fundamental human condition and should be celebrated as such. Guiding the reader through the history and psychology of error, from Socrates to Alan Greenspan, Being Wrong will change the way you perceive screw-ups, both of the mammoth and daily variety, forever.

    We think we're making smart, rational choices. But are we?In a series of illuminating, often surprising experiments, MIT behavioral economist Dan Ariely refutes the common assumption that we behave in fundamentally rational ways. Blending everyday experience with groundbreaking research, Ariely explains how expectations, emotions, social norms, and other invisible, seemingly illogical forces skew our reasoning abilities.Not only do we make astonishingly simple mistakes every day, but we make the same "types" of mistakes, Ariely discovers. We consistently overpay, underestimate, and procrastinate. We fail to understand the profound effects of our emotions on what we want, and we overvalue what we already own. Yet these misguided behaviors are neither random nor senseless. They're systematic and predictable--making us "predictably" irrational.From drinking coffee to losing weight, from buying a car to choosing a romantic partner, Ariely explains how to break through these systematic patterns of thought to make better decisions. "Predictably Irrational" will change the way we interact with the world--one small decision at a time.

    The authors present updated coverage of compilers based on research and techniques that have been developed in the field over the past few years. The book provides a thorough introduction to compiler design and covers topics such as context-free grammars, fine state machines, and syntax-directed translation.

    The human brain has some capabilities that the brains of other animals lack. It is to these distinctive capabilities that our species owes its dominant position. If machine brains surpassed human brains in general intelligence, then this new superintelligence could become extremely powerful--possibly beyond our control. As the fate of the gorillas now depends more on humans than on the species itself, so would the fate of humankind depend on the actions of the machine superintelligence.But we have one advantage: we get to make the first move. Will it be possible to construct a seed Artificial Intelligence, to engineer initial conditions so as to make an intelligence explosion survivable? How could one achieve a controlled detonation?

    The novel approach taken here banishes determinants to the end of the book and focuses on the central goal of linear algebra: understanding the structure of linear operators on vector spaces. The author has taken unusual care to motivate concepts and to simplify proofs. For example, the book presents - without having defined determinants - a clean proof that every linear operator on a finite-dimensional complex vector space (or an odd-dimensional real vector space) has an eigenvalue. A variety of interesting exercises in each chapter helps students understand and manipulate the objects of linear algebra. This second edition includes a new section on orthogonal projections and minimization problems. The sections on self-adjoint operators, normal operators, and the spectral theorem have been rewritten. New examples and new exercises have been added, several proofs have been simplified, and hundreds of minor improvements have been made throughout the text.

    Albert-László Barabási, the nation’s foremost expert in the new science of networks and author of Bursts, takes us on an intellectual adventure to prove that social networks, corporations, and living organisms are more similar than previously thought. Grasping a full understanding of network science will someday allow us to design blue-chip businesses, stop the outbreak of deadly diseases, and influence the exchange of ideas and information. Just as James Gleick and the Erdos–Rényi model brought the discovery of chaos theory to the general public, Linked tells the story of the true science of the future and of experiments in statistical mechanics on the internet, all vital parts of what would eventually be called the Barabási–Albert model.

    The pass was intercepted and the Seahawks lost. Critics called it the dumbest play in history. But was the call really that bad? Or did Carroll actually make a great move that was ruined by bad luck?Even the best decision doesn't yield the best outcome every time. There's always an element of luck that you can't control, and there is always information that is hidden from view. So the key to long-term success (and avoiding worrying yourself to death) is to think in bets: How sure am I? What are the possible ways things could turn out? What decision has the highest odds of success? Did I land in the unlucky 10% on the strategy that works 90% of the time? Or is my success attributable to dumb luck rather than great decision making?Annie Duke, a former World Series of Poker champion turned business consultant, draws on examples from business, sports, politics, and (of course) poker to share tools anyone can use to embrace uncertainty and make better decisions. For most people, it's difficult to say "I'm not sure" in a world that values and, even, rewards the appearance of certainty. But professional poker players are comfortable with the fact that great decisions don't always lead to great outcomes and bad decisions don't always lead to bad outcomes.By shifting your thinking from a need for certainty to a goal of accurately assessing what you know and what you don't, you'll be less vulnerable to reactive emotions, knee-jerk biases, and destructive habits in your decision making. You'll become more confident, calm, compassionate and successful in the long run.

    Our Big Bang, our distant future, parallel worlds, the sub-atomic and intergalactic - none of them are what they seem. But there is a way to understand this immense strangeness - mathematics. Seeking an answer to the fundamental puzzle of why our universe seems so mathematical, Tegmark proposes a radical idea: that our physical world not only is described by mathematics, but that it is mathematics. This may offer answers to our deepest questions: How large is reality? What is everything made of? Why is our universe the way it is?Table of ContentsPreface 1 What Is Reality? Not What It Seems • What’s the Ultimate Question? • The Journey Begins Part One: Zooming Out 2 Our Place in Space Cosmic Questions • How Big Is Space? • The Size of Earth • Distance to the Moon • Distance to the Sun and the Planets • Distance to the Stars • Distance to the Galaxies • What Is Space? 3 Our Place in TimeWhere Did Our Solar System Come From? • Where Did theGalaxies Come From? • Where Did the Mysterious MicrowavesCome From? • Where Did the Atoms Come From? 4 Our Universe by NumbersWanted: Precision Cosmology • Precision Microwave-Background Fluctuations • Precision Galaxy Clustering • The Ultimate Map of Our Universe • Where Did Our Big Bang Come From? 5 Our Cosmic Origins What’s Wrong with Our Big Bang? • How Inflation Works • The Gift That Keeps on Giving • Eternal Inflation 6 Welcome to the Multiverse The Level I Multiverse • The Level II Multiverse • Multiverse Halftime Roundup Part Two: Zooming In 7 Cosmic Legos Atomic Legos • Nuclear Legos • Particle-Physics Legos • Mathematical Legos • Photon Legos • Above the Law? • Quanta and Rainbows • Making Waves • Quantum Weirdness • The Collapse of Consensus • The Weirdness Can’t Be Confined • Quantum Confusion 8 The Level III Multiverse The Level III Multiverse • The Illusion of Randomness • Quantum Censorship • The Joys of Getting Scooped • Why Your Brain Isn’t a Quantum Computer • Subject, Object and Environment • Quantum Suicide • Quantum Immortality? • Multiverses Unified • Shifting Views: Many Worlds or Many Words? Part Three: Stepping Back 9 Internal Reality, External Reality and Consensus Reality External Reality and Internal Reality • The Truth, the Whole Truth and Nothing but the Truth • Consensus Reality • Physics: Linking External to Consensus Reality 10 Physical Reality and Mathematical Reality Math, Math Everywhere! • The Mathematical Universe Hypothesis • What Is a Mathematical Structure? 11 Is Time an Illusion? How Can Physical Reality Be Mathematical? • What Are You? • Where Are You? (And What Do You Perceive?) • When Are You? 12 The Level IV Multiverse Why I Believe in the Level IV Multiverse • Exploring the Level IV Multiverse: What’s Out There? • Implications of the Level IV Multiverse • Are We Living in a Simulation? • Relation Between the MUH, the Level IV Multiverse and Other Hypotheses •Testing the Level IV Multiverse 13 Life, Our Universe and Everything How Big Is Our Physical Reality? • The Future of Physics • The Future of Our Universe—How Will It End? • The Future of Life •The Future of You—Are You Insignificant? Acknowledgments Suggestions for Further Reading Index

     Plenty of experts argue that anyone who wants to develop a skill, play an instrument, or lead their field should start early, focus intensely, and rack up as many hours of deliberate practice as possible. If you dabble or delay, you'll never catch up to the people who got a head start. But a closer look at research on the world's top performers, from professional athletes to Nobel laureates, shows that early specialization is the exception, not the rule.David Epstein examined the world's most successful athletes, artists, musicians, inventors, forecasters and scientists. He discovered that in most fields--especially those that are complex and unpredictable--generalists, not specialists, are primed to excel. Generalists often find their path late, and they juggle many interests rather than focusing on one. They're also more creative, more agile, and able to make connections their more specialized peers can't see.Provocative, rigorous, and engrossing, Range makes a compelling case for actively cultivating inefficiency. Failing a test is the best way to learn. Frequent quitters end up with the most fulfilling careers. The most impactful inventors cross domains rather than deepening their knowledge in a single area. As experts silo themselves further while computers master more of the skills once reserved for highly focused humans, people who think broadly and embrace diverse experiences and perspectives will increasingly thrive.

    We’re told that learning is all self-discipline, that we must confine ourselves to designated study areas, turn off the music, and maintain a strict ritual if we want to ace that test, memorize that presentation, or nail that piano recital.   But what if almost everything we were told about learning is wrong? And what if there was a way to achieve more with less effort?   In How We Learn, award-winning science reporter Benedict Carey sifts through decades of education research and landmark studies to uncover the truth about how our brains absorb and retain information. What he discovers is that, from the moment we are born, we are all learning quickly, efficiently, and automatically; but in our zeal to systematize the process we have ignored valuable, naturally enjoyable learning tools like forgetting, sleeping, and daydreaming. Is a dedicated desk in a quiet room really the best way to study? Can altering your routine improve your recall? Are there times when distraction is good? Is repetition necessary? Carey’s search for answers to these questions yields a wealth of strategies that make learning more a part of our everyday lives—and less of a chore.   By road testing many of the counterintuitive techniques described in this book, Carey shows how we can flex the neural muscles that make deep learning possible. Along the way he reveals why teachers should give final exams on the first day of class, why it’s wise to interleave subjects and concepts when learning any new skill, and when it’s smarter to stay up late prepping for that presentation than to rise early for one last cram session. And if this requires some suspension of disbelief, that’s because the research defies what we’ve been told, throughout our lives, about how best to learn.   The brain is not like a muscle, at least not in any straightforward sense. It is something else altogether, sensitive to mood, to timing, to circadian rhythms, as well as to location and environment. It doesn’t take orders well, to put it mildly. If the brain is a learning machine, then it is an eccentric one. In How We Learn, Benedict Carey shows us how to exploit its quirks to our advantage.  Praise for How We Learn“This book is a revelation. I feel as if I’ve owned a brain for fifty-four years and only now discovered the operating manual.”—Mary Roach, bestselling author of Stiff and Gulp“A welcome rejoinder to the faddish notion that learning is all about the hours put in.” —The New York Times Book Review   “A valuable, entertaining tool for educators, students and parents.” —Shelf Awareness   “How We Learn is more than a new approach to learning; it is a guide to making the most out of life. Who wouldn’t be interested in that?” —Scientific American   “I know of no other source that pulls together so much of what we know about the science of memory and couples it with practical, practicable advice.”—Daniel T. Willingham, professor of psychology at the University of Virginia

    It's Tuesday morning and on his drive into the office, Bill gets a call from the CEO. The company's new IT initiative, code named Phoenix Project, is critical to the future of Parts Unlimited, but the project is massively over budget and very late. The CEO wants Bill to report directly to him and fix the mess in ninety days or else Bill's entire department will be outsourced. With the help of a prospective board member and his mysterious philosophy of The Three Ways, Bill starts to see that IT work has more in common with manufacturing plant work than he ever imagined. With the clock ticking, Bill must organize work flow streamline interdepartmental communications, and effectively serve the other business functions at Parts Unlimited. In a fast-paced and entertaining style, three luminaries of the DevOps movement deliver a story that anyone who works in IT will recognize. Readers will not only learn how to improve their own IT organizations, they'll never view IT the same way again.

    It is a book for everybody who wants to learn how to write or who needs to do some writing to get through the day, as almost everybody does in the age of e-mail and the Internet. Whether you want to write about people or places, science and technology, business, sports, the arts or about yourself in the increasingly popular memoir genre, On Writing Well offers you fundamental priciples as well as the insights of a distinguished writer and teacher. With more than a million copies sold, this volume has stood the test of time and remains a valuable resource for writers and would-be writers.

    He also crystallized one of the most important debates of our time: As we enjoy the Net’s bounties, are we sacrificing our ability to read and think deeply?Now, Carr expands his argument into the most compelling exploration of the Internet’s intellectual and cultural consequences yet published. As he describes how human thought has been shaped through the centuries by “tools of the mind”—from the alphabet to maps, to the printing press, the clock, and the computer—Carr interweaves a fascinating account of recent discoveries in neuroscience by such pioneers as Michael Merzenich and Eric Kandel. Our brains, the historical and scientific evidence reveals, change in response to our experiences. The technologies we use to find, store, and share information can literally reroute our neural pathways.Building on the insights of thinkers from Plato to McLuhan, Carr makes a convincing case that every information technology carries an intellectual ethic—a set of assumptions about the nature of knowledge and intelligence. He explains how the printed book served to focus our attention, promoting deep and creative thought. In stark contrast, the Internet encourages the rapid, distracted sampling of small bits of information from many sources. Its ethic is that of the industrialist, an ethic of speed and efficiency, of optimized production and consumption—and now the Net is remaking us in its own image. We are becoming ever more adept at scanning and skimming, but what we are losing is our capacity for concentration, contemplation, and reflection.Part intellectual history, part popular science, and part cultural criticism, The Shallows sparkles with memorable vignettes—Friedrich Nietzsche wrestling with a typewriter, Sigmund Freud dissecting the brains of sea creatures, Nathaniel Hawthorne contemplating the thunderous approach of a steam locomotive—even as it plumbs profound questions about the state of our modern psyche. This is a book that will forever alter the way we think about media and our minds.